code: def test_fsdp_fake_e2e(self):
      store = dist.HashStore()
      dist.init_process_group(
          backend="fake", rank=0, world_size=2, store=store
      )
      my_module = nn.Sequential(
          nn.Linear(2, 3, device="cuda"),
          nn.ReLU(),
          nn.Linear(3, 2, device="cuda"),
      )
      sharded_module = FSDP(my_module, use_orig_params=True)
      optim = torch.optim.Adam(sharded_module.parameters(), lr=0.0001)
      input = torch.randn(2, 2)
      x = sharded_module(input)
      loss = x.sum()
      loss.backward()
      optim.step()
  
imports: import sys
  import torch
  import torch.distributed
  import torch.nn
  import unittest
  import torch.distributed._functional_collectives
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing._internal.distributed.fake_pg import FakeStore
  from torch.testing import FileCheck
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.distributed._tensor import DeviceMesh, init_device_mesh, Shard
  from torch.testing._internal.common_utils import TestCase, run_tests
  from torch.distributed.tensor.parallel import ColwiseParallel, parallelize_module, RowwiseParallel
  from torch.testing._internal.distributed._tensor.common_dtensor import MLPModule
label_desc: Use image node_id 6 for calling the TestFakePG obj's underlying member method code with example usage: obj.test_fsdp_fake_e2e() without return types